DATA → DECISION → OPTIMIZATION.
I use performance data to identify what isn’t working, make a strategic adjustment, measure the response — and optimize again.
Kelsey-White was a simulated consumer-goods company, and “Blue” was its laundry detergent brand. As Brand Manager, I used customer, channel, pricing and competitor sales data to decide who to target, which detergent formats to prioritize, how to price the product and how to respond as market performance changed.
Laundry Detergent · Brand Manager · SimulationPods + liquid formats · odor elimination positioning · consumer household targeting · pricing and market-share optimization.
First-year profit growth
Optimized pricing + product mix
Cumulative operating profit
Across four years
Absolute market-share gain
Within 12 months
75% of profit from <$39,999 income; 70% from under-44s; 86% from 3+ households. Digital delivered 11.5M reach.
Prioritize younger, larger, value-conscious households and the strongest regions.
$7–$7.50 pricing, pods/liquid focus, odor-elimination USP and regional targeting.
$305M peak annual revenue and +111% first-year profit growth.
Pricing, product and competitive decisions culminated in +2.7-point share growth.
A strategy and analytics project built from a cleaned global cycling-retail database of 112,036 orders. I isolated a high-value “Golden Cohort,” then translated the analysis into separate acquisition, pricing and volume strategies across bikes, accessories and clothing.
Growth Strategy · Customer Analytics · ROI OptimizationRather than treating 112,036 global orders as one audience, I looked for the intersection of the customer and geographic variables associated with the strongest value.
$16,350,435 in profit concentrated inside the cohort. That concentration became the basis for the growth strategy.
Of total database profit
Generated by Golden Cohort
Bike profit inside cohort
Largest product driver
Expected business-growth
Mandate
Start with the cleaned 112,036-order database and compare customer value across age and geography rather than assuming the whole customer base behaves alike.
Identify ages 24–43 as the top-performing age band, then intersect it with the top 25% of geographies to form the Golden Cohort.
Break the cohort's $16.35M profit into product roles: bikes $10.81M, accessories $4.19M and clothing $1.34M.
Use those roles to assign different levers: bike acquisition, accessory price-elasticity testing and clothing volume expansion.
Scale each lever only where the underlying cohort, regional order depth and product economics support it.
Analysis of 7,000+ customer records to identify who was most at risk, what was driving that risk, and where retention strategy should intervene.
Business Solutions & Marketing Analyst · Dataset AnalysisMonth-to-month customers
More likely to churn
Odds ratio
Two-year contract
Churned customers
Not accounted for by model
Month-to-month contracts, fibre optic service and electronic checks carried highest risk.
Prioritize Churn City, Churn Line VIPs and senior customers.
Contract promotion, more tech-support touchpoints and segment-triggered offers.
Longer tenure and support interaction were associated with sharply lower churn risk.
The unexplained churn gap becomes the next analytical problem.
Brand and business-development strategy for a handmade jewelry business with strong face-to-face conversion and a critical winter sales bottleneck.
Business Development & Brand Strategist · Sep–Dec 2025Instagram audience objective
By mid-November
TikTok audience objective
By mid-November
Weekly online-sales objective
Equal to one full market day
High in-person conversion and a viral founder story contrasted with winter production and sales constraints.
Translate the founder-led experience into a feasible year-round digital process.
Standardize identity and voice, build educational content, overhaul the site and digitize the catalogue.
The digital offer shifted toward the core handcrafted jewelry collection with usable inventory infrastructure.
The system created capacity for creator onboarding, content days and community expansion.
I combine marketing analytics, consumer insight and creative strategy to understand performance — then use what the data says to sharpen the next move.